How Earthquakes are Predicted Using Geological Data

In the last few decades, the intensity, frequency, and occurrence of natural disasters have increased so much. For instance, more than 4000 natural disasters occurred between 2001 and 2010, causing more than one million deaths. Earthquakes are caused by population growth, industrialization and urbanization. Some of these disasters occur abruptly and affect many people. Therefore, it is crucial to develop a Geological data System which will have the geographical data of areas suspected to be affected by natural disasters such as earthquakes. The Geographic Information system is a valuable tool which is used to predict earthquakes. Perhaps, to use GIS, for earthquakes prediction, previous data and information about the patterns and occurrence of earthquake in various regions in the world should be available. Geologic data such as area mapping is needed to evaluate and predict area vulnerable to earthquakes. Satellite images classification alongside other map information such as geomorphology will provide adequate information which is used to predict the subsequent earthquake occurrence. Besides, geologic data is used to predict the location, date and time, and the magnitude of the earthquake.

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The geological data can be used to determine the seismicity of an earthquake. Almost all earthquakes take place on faults; therefore, the seismicity of an earthquake can be determined through mapping and identification of the active faults in regions which are vulnerable to earthquakes. Geological data provides essential information about the earthquakes which will help to predict the future pattern and occurrence of earthquakes. Based on the geological data, the seismic risks of specific areas are quantified statistically to determine the active faults and consequently predict the occurrence of an outbreak (Akkar, Polat and Torild). For instance, this information can be used to determine the chances of an earthquake occurring in the next ten years in a seismic location. Further, pre-earthquake indicators such as a change in random gas, ground hitting, and change in seismic activities are also crucial geological data which are used to predict future earthquake occurrence. As far as the geological data is concerned, geologists can determine the time and map the areas on earth where an earthquake is likely to occur.

Geoscientists conduct frequent researches to determine the causes of earthquakes and the possible way to predict earthquakes before they happen because once it has happened, it causes massive destruction. Geoscientists can be able to identify the area which is at risk using the previous geological data. Earthquake forecasting or prediction is solely based on the data gathered through the global seismic monitoring networks, historical records, geological field works, and high-density earthquake monitoring (Stefansson). Earthquake prediction has improved because of the understanding and utilization of geological data and testing of the geological models through observation. Besides, geological data help the geoscientists to identify the diagnostic precursor, which will indicate the higher chances of a significant or minor earthquake happening at a specific region and time. The principle of research and gathering of geologic data is improving, and earthquake prediction and forecasting are done easily now than before. Further, laboratory experiments using geological data attempts to understand the physical processes which help in the prediction and forecasting of earthquakes. The geological data has also helped the geoscientists to that a series of minor earthquakes usually precede a massive earthquake.

Geological data can also be used during seismic monitoring and research to provide a basis for earthquake prediction and mapping of the area which are at risk of earthquake occurrence. Geological data can be categorized into various priority indicating areas which are likely to experience significant earthquakes and that one that is like to experience minor earthquakes. The geological data is also vital because it contains accurate and timely information about the previous seismic events, which will help in predicting the chances of another earthquake happening at a specific place. Additionally, the global seismic network provides accurate and high-quality geological data from various regions around the world which are used by geoscientists to predict the future occurrence of earthquakes (Mary). Geological data is used to determine the size of the destructive earthquakes and the time these earthquakes are likely to occur. Seismic monitoring and research will also provide the frequency of earthquake occurrence around the glebe enabling the geoscientists to determine the time when the next earthquake is likely to occur. Ultimately seismic monitoring and research play a critical role in earthquake prediction and mitigation.

Conclusion

Earthquakes are a severe natural disaster which has the potential to cause mass destruction, including deaths. It is crucial to gather accurate and relevant geological data which will help to predict the future occurrence, preparedness and mitigation of the earthquakes. The geological data is vital in determining and predicting the future seismicity of an earthquake. Geoscientists use geological data to map areas which are vulnerable to earthquakes. In some seismic area, it is possible to identify the patterns which make it easier to predict when another earthquake is likely to occur. Ultimately, earthquake prediction has dramatically improved because of the availability of geological data.

Works Cited

Akkar, Sinan, Polat Gulkan, and Torild Van Eck, eds. Earthquake Data in Engineering Seismology: Predictive Models, Data Management and Networks. Vol. 14. Springer Science & Business Media, 2011.

Lazaridou-Varotsos, Mary S. Earthquake Prediction by Seismic Electric Signals: The success of the VAN method over thirty years. Springer Science & Business Media, 2012.

Stefansson, Ragnar. Advances in earthquake prediction: research and risk mitigation. Springer Science & Business Media, 2011.